Job Description
Note: The job is a remote job and is open to candidates in USA. Zillow is a leading real estate platform dedicated to transforming how people navigate the real estate market. The Machine Learning Engineer will design and implement production machine learning models to enhance core product features, collaborating with cross-functional teams to optimize user experiences and improve infrastructure.
Responsibilities
- Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications
- Help re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces
- Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
- Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
- Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
- Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap
- Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling
Skills
- 1-3 years of experience in developing applications in search, personalized ranking, or recommender systems
- Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
- Strong programming skills in a high-level language such as Python or Java
- Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
- Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
- Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
- A Master's degree + 2 yrs or BS with a minimum of 4 yrs of experience (preferably in large consumer tech companies)
- Prior experience or high level of curiosity with generative AI and excitement to collaborate on what they've learned!
Benefits
- Equity awards based on factors such as experience, performance and location
Company Overview
Company H1B Sponsorship
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